Load necessary packages.
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## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(plotly)##
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## filter
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## layoutlibrary(dplyr)
library(ggplot2)
library(tidyr)
library(scales)##
## Attaching package: 'scales'
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## col_factorknitr::opts_chunk$set(
fig.width = 10,
fig.asp = .8,
out.width = "90%"
)Read the dataset and drop NA vlaues.
youtube_df <- read_csv("Data/cleaned_youtube_df.csv")|>
janitor::clean_names()|>
drop_na()## Rows: 995 Columns: 18
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): category, country, abbreviation, channel_type
## dbl (14): id, subscribers, video_views, uploads, video_views_for_the_last_30...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.summary(youtube_df)## id subscribers video_views category
## Min. : 1.0 Min. : 12300000 Min. :2.634e+03 Length:589
## 1st Qu.:213.0 1st Qu.: 14700000 1st Qu.:4.910e+09 Class :character
## Median :454.0 Median : 18600000 Median :8.761e+09 Mode :character
## Mean :471.2 Mean : 24264516 Mean :1.280e+10
## 3rd Qu.:723.0 3rd Qu.: 26400000 3rd Qu.:1.507e+10
## Max. :995.0 Max. :245000000 Max. :2.280e+11
## uploads country abbreviation channel_type
## Min. : 1 Length:589 Length:589 Length:589
## 1st Qu.: 433 Class :character Class :character Class :character
## Median : 1189 Mode :character Mode :character Mode :character
## Mean : 13945
## 3rd Qu.: 3882
## Max. :301308
## video_views_for_the_last_30_days lowest_monthly_earnings
## Min. :3.000e+00 Min. : 0
## 1st Qu.:4.845e+07 1st Qu.: 11500
## Median :1.143e+08 Median : 28200
## Mean :2.446e+08 Mean : 54260
## 3rd Qu.:2.441e+08 3rd Qu.: 59000
## Max. :6.589e+09 Max. :850900
## highest_monthly_earnings lowest_yearly_earnings highest_yearly_earnings
## Min. : 0 Min. : 0 Min. : 0
## 1st Qu.: 183200 1st Qu.: 137400 1st Qu.: 2200000
## Median : 451100 Median : 338300 Median : 5400000
## Mean : 867499 Mean : 650618 Mean : 10417717
## 3rd Qu.: 944000 3rd Qu.: 708000 3rd Qu.: 11300000
## Max. :13600000 Max. :10200000 Max. :163400000
## subscribers_for_last_30_days created_year population
## Min. : 1 Min. :1970 Min. :2.025e+05
## 1st Qu.: 100000 1st Qu.:2010 1st Qu.:1.081e+08
## Median : 200000 Median :2013 Median :3.282e+08
## Mean : 356695 Mean :2013 Mean :4.906e+08
## 3rd Qu.: 400000 3rd Qu.:2016 3rd Qu.:3.282e+08
## Max. :8000000 Max. :2022 Max. :1.398e+09
## latitude longitude
## Min. :-38.42 Min. :-172.105
## 1st Qu.: 20.59 1st Qu.: -95.713
## Median : 30.59 Median : -3.436
## Mean : 26.21 Mean : -6.254
## 3rd Qu.: 37.09 3rd Qu.: 78.963
## Max. : 61.52 Max. : 138.253Visualize Numeric Data
all_columns <- colnames(youtube_df)
columns_to_plot <- all_columns[!all_columns %in% c("id", "category","country","abbreviation","channel_type","population","latitude","longitude")]
numeric_data_long <- youtube_df[, columns_to_plot] %>%
gather(key = "variable", value = "value")
color <- "steelblue"
# Create a single plot with facets for each numeric variable
p <- ggplot(numeric_data_long, aes(x = value)) +
geom_histogram(aes(y = ..density..),bins = 20, fill = "#8dab7f", alpha = 0.8) +
geom_density(color="#6b8e23")+
facet_wrap(~ variable, scales = "free", ncol = 3) +
scale_x_continuous(labels = scales::comma) +
theme_minimal(base_size = 10) +
theme(
strip.text.x = element_text(size = 10, face = "bold"),
axis.text.x = element_text(angle = 45, hjust = 1, vjust = 1,size=6,face = "bold"), # Angle x-axis labels for readability
axis.title.x = element_text(size = 12),
axis.title.y = element_text(size = 12),
plot.title = element_text(size = 16, face = "bold"),
plot.margin = margin(2.5, 2.5, 2.5, 2.5, "cm"), # Adjust the plot margins
strip.background = element_blank(),
panel.spacing = unit(2, "lines")
) +
labs(
title = "Distribution of Numeric Variables",
x = "Value",
y = "Frequency",
caption = "Source: YouTube Data"
)
# Convert to an interactive plot
ggplotly(p)## Warning: The dot-dot notation (`..density..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(density)` instead.
## ℹ The deprecated feature was likely used in the ggplot2 package.
## Please report the issue at <https://github.com/tidyverse/ggplot2/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.